基于商品特征关联度的购物客户评论可信排序方法

doi:10.11772/j.issn.1001-9081.2014.08.2322

计算机应用 ›› 2014, Vol. 34 ›› Issue (8): 2322-2327.DOI: 10.11772/j.issn.1001-9081.2014.08.2322

基于商品特征关联度的购物客户评论可信排序方法

黄婷婷¹,²,曾国荪¹,²,熊焕亮¹,²

1. 国家高性能计算机工程技术研究中心同济分中心，上海200092
2. 同济大学计算机科学与技术系，上海200092

收稿日期:2014-03-10 修回日期:2014-04-22 出版日期:2014-08-01 发布日期:2014-08-10
通讯作者: 黄婷婷
作者简介:黄婷婷(1989-)，女，江西新余人，硕士研究生，主要研究方向：电子商务、内容信任；曾国荪（1964-），男，江西吉安人，教授，博士生导师，博士，主要研究方向：并行计算、可信软件、信息安全；熊焕亮（1977-），男，江西新建人，博士研究生，主要研究方向：并行分布处理、云计算、可信软件。
基金资助:
国家863计划项目;国家自然科学基金资助项目;上海市优秀学科带头人计划项目;教育部网络时代的科技论文快速共享专项研究课题项目;华为创新研究计划项目

Trustworthy sort method for shopping customer reviews based on correlation degree with product features

HUANG Tingting¹,²,ZENG Guosun¹,²,XIONG Huanliang¹,²

1. Department of Computer Science and Technology, Tongji University, Shanghai 200092, China;
2. Tongji Branch, National Engineering and Technology Center of High Performance Computer, Shanghai 200092, China

Received:2014-03-10 Revised:2014-04-22 Online:2014-08-01 Published:2014-08-10
Contact: HUANG Tingting

摘要/Abstract

摘要：

电子商务网站中，海量无序的用户评论可能导致消费者客户“迷失”其中，无法识别评论的可信和真假。针对这个问题，提出了一种根据用户评论的可信度对其重新排序的方法。首先，针对网站商品广告信息，关注在线用户评论内容是否和商品功能属性密切相关，设计了基于HTML脚本格式的购物网站中商品关键特征提取算法，给出了基于自然语言处理的用户评论特征词提取方法；然后，利用词语相似度来分析商品特征和用户评论内容之间的关联度，提出了购物客户评论的可信度计算方法；最后，通过实例分析，实现了大量购物客户评论的可信排序，使得用户无须浏览全部或者大部分之后就能判断哪些评价可以信任或者具有实际的参考价值，降低了信息搜索成本，提高了决策效率。

Abstract:

In E-commerce website, massive disorder shopping reviews may make the consumers be lost in the massive shopping reviews and can not distinguish trusted reviews. Therefore, this paper proposed a trustworthy sort method for customer reviews. Firstly, focusing on commercial advertising information in websites and concerning about whether the contents of the online customer reviews and product functional properties are closely related, the authors designed an algorithm of product's key features extractions from shopping websites based on HTML script format, and presented a method of customer reviews features extractions based on natural language processing. Secondly, the authors used the technique of words similarity to analyze the correlation degree between product features and customer reviews contents, and then proposed the computational method of trust degree for shopping customer reviews. Finally, through analyzing the method with an example, the proposed method achieves a trustworthy sort for large online shopping customer reviews. Thus customers need not browse all reviews to judge which one can be trusted or have the real reference value. It decreases information search costs and improves the efficiency of decision making.

中图分类号:

TP291
TP18v

黄婷婷曾国荪熊焕亮. 基于商品特征关联度的购物客户评论可信排序方法[J]. 计算机应用, 2014, 34(8): 2322-2327.

HUANG Tingting ZENG Guosun XIONG Huanliang. Trustworthy sort method for shopping customer reviews based on correlation degree with product features[J]. Journal of Computer Applications, 2014, 34(8): 2322-2327.

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基于商品特征关联度的购物客户评论可信排序方法

Trustworthy sort method for shopping customer reviews based on correlation degree with product features

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